In [1]:
!pip install scikit-optimize
Requirement already satisfied: scikit-optimize in /opt/anaconda3/lib/python3.12/site-packages (0.10.2)
Requirement already satisfied: joblib>=0.11 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-optimize) (1.4.2)
Requirement already satisfied: pyaml>=16.9 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-optimize) (25.1.0)
Requirement already satisfied: numpy>=1.20.3 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-optimize) (1.26.4)
Requirement already satisfied: scipy>=1.1.0 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-optimize) (1.13.1)
Requirement already satisfied: scikit-learn>=1.0.0 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-optimize) (1.5.1)
Requirement already satisfied: packaging>=21.3 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-optimize) (24.1)
Requirement already satisfied: PyYAML in /opt/anaconda3/lib/python3.12/site-packages (from pyaml>=16.9->scikit-optimize) (6.0.1)
Requirement already satisfied: threadpoolctl>=3.1.0 in /opt/anaconda3/lib/python3.12/site-packages (from scikit-learn>=1.0.0->scikit-optimize) (3.5.0)
In [3]:
import pandas as pd
file_path = '/Users/fizza/path/to/data_ML_FZA.csv'
data = pd.read_csv(file_path)

def clean_target(value):
    if value in ['xx', 'xx', 'xx']:
        return 0.01  
    try:
        return float(value)
    except ValueError:
        return None

data['y1'] = data['y1'].apply(clean_target)

data = data.dropna(subset=['y1'])
data['y1'] = data['y1'].astype(float)

data.info(), data['y1'].describe()
<class 'pandas.core.frame.DataFrame'>
RangeIndex: 267 entries, 0 to 266
Data columns (total 67 columns):
 #   Column             Non-Null Count  Dtype  
---  ------             --------------  -----  
 0   y1                 267 non-null    float64
 1   New a-ratio (%)    267 non-null    int64  
 2   Unnamed: 25        0 non-null      float64
 3   x1_STol            267 non-null    bool   
 4   x2_a               267 non-null    bool   
 5   x2_b               267 non-null    bool   
 6   x3_H               267 non-null    bool   
 7   x3_N3              267 non-null    bool   
 8   x3_OBn             267 non-null    bool   
 9   x4_equatorial      267 non-null    bool   
 10  x5_OBn             267 non-null    bool   
 11  x6_OBn             267 non-null    bool   
 12  x7_axial           267 non-null    bool   
 13  x7_equatorial      267 non-null    bool   
 14  x8_CH3             267 non-null    bool   
 15  x8_OBn             267 non-null    bool   
 16  x9_270             267 non-null    bool   
 17  x9_2656            267 non-null    bool   
 18  x9_17000           267 non-null    bool   
 19  x9_72000           267 non-null    bool   
 20  x9_1000000         267 non-null    bool   
 21  x10_-              267 non-null    bool   
 22  x10_OMe            267 non-null    bool   
 23  x11_-              267 non-null    bool   
 24  x11_a              267 non-null    bool   
 25  x12_-              267 non-null    bool   
 26  x12_OBn            267 non-null    bool   
 27  x13_-              267 non-null    bool   
 28  x13_OBn            267 non-null    bool   
 29  x14_-              267 non-null    bool   
 30  x14_OBn            267 non-null    bool   
 31  x14_OH             267 non-null    bool   
 32  x15_-              267 non-null    bool   
 33  x15_OBn            267 non-null    bool   
 34  x15_OH             267 non-null    bool   
 35  x16_1_OH           267 non-null    bool   
 36  x16_4_OH           267 non-null    bool   
 37  x16_6_OH           267 non-null    bool   
 38  x17_Secondary      267 non-null    bool   
 39  x17_primary        267 non-null    bool   
 40  x17_secondary      267 non-null    bool   
 41  x17_tertiary       267 non-null    bool   
 42  x18_1.0            267 non-null    bool   
 43  x18_1.36           267 non-null    bool   
 44  x18_3.51           267 non-null    bool   
 45  x18_7.16           267 non-null    bool   
 46  x18_80.0           267 non-null    bool   
 47  x18_100.0          267 non-null    bool   
 48  x19_-20 ℃          267 non-null    bool   
 49  x19_-40 ℃          267 non-null    bool   
 50  x19_0 ℃            267 non-null    bool   
 51  x19_25 ℃           267 non-null    bool   
 52  x20_DCM            267 non-null    bool   
 53  x20_DCM/ACN        267 non-null    bool   
 54  x20_DCM/DMF        267 non-null    bool   
 55  x20_DCM/p-Dioxane  267 non-null    bool   
 56  x20_THF            267 non-null    bool   
 57  x20_Toluene        267 non-null    bool   
 58  x21_0.018M         267 non-null    bool   
 59  x21_0.036M         267 non-null    bool   
 60  x21_0.051M         267 non-null    bool   
 61  x21_0.167M         267 non-null    bool   
 62  x21_0.308M         267 non-null    bool   
 63  x22_1:0.66         267 non-null    bool   
 64  x22_1:1.5          267 non-null    bool   
 65  x23_IDCP           267 non-null    bool   
 66  x23_NIS_TfOH       267 non-null    bool   
dtypes: bool(64), float64(2), int64(1)
memory usage: 23.1 KB
Out[3]:
(None,
 count    267.000000
 mean      51.592547
 std       31.597137
 min        0.000000
 25%       27.000000
 50%       55.000000
 75%       75.000000
 max      100.000000
 Name: y1, dtype: float64)
In [5]:
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestRegressor
import matplotlib.pyplot as plt
from IPython.display import display, HTML

file_path = '/Users/fizza/path/to/data_ML_FZA.csv'
data = pd.read_csv(file_path)

def clean_target(value):
    if value in ['xx', 'xx', 'xx']:
        return 0.01 
    try:
        return float(value)
    except ValueError:
        return None

data['y1'] = data['y1'].apply(clean_target)

data = data.dropna(subset=['y1'])
data['y1'] = data['y1'].astype(float)

X = data.drop(columns=['y1'])
y = data['y1']

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.1, random_state=42)

model = RandomForestRegressor(random_state=42)
model.fit(X_train, y_train)

new_data_path = '/Users/fizza/path/to/data_ML_FZA.cs/vencoded_data_ML_FZA.csv'
new_data = pd.read_csv(new_data_path)

if 'y1' in new_data.columns:
    new_data['y1'] = new_data['y1'].apply(clean_target)

new_data_encoded = pd.get_dummies(new_data)

missing_cols = set(X.columns) - set(new_data_encoded.columns)
for col in missing_cols:
    new_data_encoded[col] = 0
new_data_encoded = new_data_encoded[X.columns]

new_pred_a_ratio = model.predict(new_data_encoded)
new_data['New a-ratio'] = new_pred_a_ratio

output_csv_path = '/Users/fizza/path/to/Predicted_alpha_ratios-FZA.csv'
new_data.to_csv(output_csv_path, index=False)

display(new_data.head())

html_link = f'<a href="file:///{output_csv_path}" download>Download the new alpha ratios CSV file</a>'

plt.figure(figsize=(10, 6))
plt.hist(new_data['New a-ratio'], bins=20, color='skyblue', edgecolor='black')
plt.xlabel('New a-ratio values')
plt.ylabel('Frequency')
plt.title('Distribution of Predicted New Alpha Ratios')
plt.show()
y1 New a-ratio (%) Unnamed: 25 x1_STol x2_a x2_b x3_H x3_N3 x3_OBn x4_equatorial ... x21_0.018M x21_0.036M x21_0.051M x21_0.167M x21_0.308M x22_1:0.66 x22_1:1.5 x23_IDCP x23_NIS_TfOH New a-ratio
0 0.0 0 NaN True False True False True False True ... False False False True False False True False True 0.0005
1 0.0 9 NaN True False True False False True True ... False False False True False False True False True 2.0209
2 62.0 52 NaN True False True False False True True ... False False False True False False True False True 58.1100
3 83.0 70 NaN True False True False False True True ... False False False True False False True False True 79.1400
4 40.0 37 NaN True True False True False False True ... False False False True False False True False True 38.8200

5 rows × 68 columns

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In [8]:
import pandas as pd
import numpy as np
from sklearn.ensemble import RandomForestRegressor
from sklearn.model_selection import train_test_split, GridSearchCV
from sklearn.metrics import mean_squared_error, r2_score
import matplotlib.pyplot as plt
from scipy.stats import linregress

def clean_target(value):
    if value in ['No Reaction', 'Trace', 'Later']:
        return np.nan 
    try:
        return float(value)
    except ValueError:
        return np.nan

data = pd.read_csv('/Users/fizza/path/to/predicted_alpha_ratios.csv')
data['y1'] = data['y1'].apply(clean_target)

data = data.dropna(subset=['y1'])

data = data.apply(pd.to_numeric, errors='coerce')
data.fillna(data.mean(), inplace=True)

X = data.drop(columns=['y1'])
y = data['y1']

X_train, X_test, y_train, y_test = train_test_split(
    X, y,
    test_size=0.3,
    random_state=42
)

param_grid = {
    'n_estimators': [100, 200, 500],
    'max_depth': [10, 20, None],
    'min_samples_split': [2, 5, 10],
    'min_samples_leaf': [1, 2, 4]
}

grid_search = GridSearchCV(
    RandomForestRegressor(random_state=42),
    param_grid,
    cv=5,
    scoring='neg_mean_squared_error',
    verbose=2,
    n_jobs=-1
)
grid_search.fit(X_train, y_train)

best_model = grid_search.best_estimator_
print("Best Parameters:", grid_search.best_params_)

y_train_pred = best_model.predict(X_train)
y_test_pred = best_model.predict(X_test)

all_actual = np.concatenate([y_train, y_test])
all_predicted = np.concatenate([y_train_pred, y_test_pred])

r2 = r2_score(all_actual, all_predicted)
mse = mean_squared_error(all_actual, all_predicted)
rmse = np.sqrt(mse)
print(f"R²: {r2:.3f}")
print(f"RMSE: {rmse:.3f}")

slope, intercept, r_value, _, _ = linregress(all_actual, all_predicted)

plt.figure(figsize=(4, 3), dpi=800)
plt.scatter(all_actual, all_predicted, alpha=0.7, color='green', label='Data points')
plt.plot(
    [all_actual.min(), all_actual.max()],
    [all_actual.min(), all_actual.max()],
    color='gray', linestyle='--', label='Perfect prediction'
)
metrics_text = (
    f"$R^2$: {r2:.3f}\n"
    f"RMSE: {rmse:.3f}\n"
    f"Slope: {slope:.3f}\n"
    f"Pearson r: {r_value:.3f}"
)
plt.gca().text(
    0.96, 0.05, metrics_text, transform=plt.gca().transAxes, fontsize=8,
    verticalalignment='bottom', horizontalalignment='right',
    bbox=dict(boxstyle='round,pad=0.5', edgecolor='black', facecolor='white')
)
plt.xlabel('Actual α-ratio (%)', fontsize=10)
plt.ylabel('Predicted α-ratio (%)', fontsize=10)
plt.tight_layout()
plt.show()
Fitting 5 folds for each of 81 candidates, totalling 405 fits
Best Parameters: {'max_depth': 10, 'min_samples_leaf': 2, 'min_samples_split': 5, 'n_estimators': 500}
R²: 0.936
RMSE: 7.977
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In [9]:
from sklearn.metrics import r2_score, mean_squared_error
import matplotlib.pyplot as plt
from scipy.stats import linregress
import numpy as np

r2_train = r2_score(y_train, y_train_pred)
r2_test = r2_score(y_test, y_test_pred)

rmse_train = np.sqrt(mean_squared_error(y_train, y_train_pred))
rmse_test = np.sqrt(mean_squared_error(y_test, y_test_pred))

sns.set(style="whitegrid", font_scale=1.2)
plt.figure(figsize=(5, 4), dpi=600)

plt.scatter(y_train, y_train_pred, c='#1f77b4', edgecolor='k', alpha=0.6, label=f'Training (R² = {r2_train:.2f})')
plt.scatter(y_test, y_test_pred, c='#d62728', edgecolor='k', alpha=0.6, label=f'Testing (R² = {r2_test:.2f})')

min_val = min(y_train.min(), y_test.min())
max_val = max(y_train.max(), y_test.max())
plt.plot([min_val, max_val], [min_val, max_val], linestyle='--', color='gray', label='Perfect prediction')
plt.legend(frameon=True, fontsize=10, loc='lower right')

plt.xlabel('Actual α-ratio (%)')
plt.ylabel('Predicted α-ratio (%)')
plt.title('Actual vs Predicted α-ratio')
plt.tight_layout()
plt.show()
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In [3]:
import pandas as pd
import numpy as np
import joblib
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn.metrics import r2_score, mean_squared_error
from scipy.stats import pearsonr

font_size = 15
xlim = (0, 100)
ylim = (0, 100)
max_points = 800

file_path = '/Users/fizza/path/to/Gly-data a_ratio2.csv'
df = pd.read_csv(file_path)

target_col = 'y1'
base_a_ratio_series = pd.to_numeric(df[target_col], errors='coerce')
df = df.loc[base_a_ratio_series.dropna().index]
base_a_ratio = base_a_ratio_series.dropna().values
feature_cols = df.columns.drop(target_col)
X = df[feature_cols]

rf_model = joblib.load('/Users/fizza/path/to/random_forest_model.pkl')
xgb_model = joblib.load('/Users/fizza/path/to/xgboost_model.pkl')
ridge_model = joblib.load('/Users/fizza/path/to/ridge_model.pkl')
lasso_model = joblib.load('/Users/fizza/path/to/lasso_model.pkl')
catboost_model = joblib.load('/Users/fizza/path/to/catboost_model.pkl')
gb_model = joblib.load('/Users/fizza/path/to/gradient_boosting_model.pkl')
svr_model = joblib.load('/Users/fizza/path/to/svr_model.pkl')
dt_model = joblib.load('/Users/fizza/path/to/decision_tree_model.pkl')
ada_model = joblib.load('/Users/fizza/path/to/adaboost_model.pkl')

rf_pred_a_ratio = rf_model.predict(X)
xgb_pred_a_ratio = xgb_model.predict(X)
ridge_pred_a_ratio = ridge_model.predict(X)
lasso_pred_a_ratio = lasso_model.predict(X)
catboost_pred_a_ratio = catboost_model.predict(X)
gb_pred_a_ratio = gb_model.predict(X)
svr_pred_a_ratio = svr_model.predict(X)
dt_pred_a_ratio = dt_model.predict(X)
ada_pred_a_ratio = ada_model.predict(X)

best_w = 0.7  
best_hybrid = best_w * rf_pred_a_ratio + (1 - best_w) * xgb_pred_a_ratio
predictions_a_ratio = {
    'Hybrid Model': best_hybrid,
    'Random Forest': rf_pred_a_ratio,
    'XGBoost': xgb_pred_a_ratio,
    'CatBoost': catboost_pred_a_ratio,
    'Gradient Boosting': gb_pred_a_ratio,
    'Ridge Regression': ridge_pred_a_ratio,
    'Lasso Regression': lasso_pred_a_ratio,
    'Support Vector Regressor': svr_pred_a_ratio,
    'Decision Tree': dt_pred_a_ratio,
    'AdaBoost': ada_pred_a_ratio,
}
df_a_ratio = pd.DataFrame({'Actual': base_a_ratio, **predictions_a_ratio})
r2_scores = {model: r2_score(df_a_ratio['Actual'], df_a_ratio[model]) for model in predictions_a_ratio}
sorted_models = sorted(predictions_a_ratio.keys(), key=lambda m: r2_scores[m], reverse=True)
colors = sns.color_palette("husl", len(sorted_models))
fig, axes = plt.subplots(2, 5, figsize=(23, 7), dpi=800)
axes = axes.flatten()
for ax, model, color in zip(axes, sorted_models, colors):
    r2 = r2_scores[model]
    n_points = min(max_points, int((r2 ** 2) * max_points), len(df_a_ratio))
    sub_df = df_a_ratio[['Actual', model]].sample(n=n_points, random_state=42)
    pred = sub_df[model]
    actual = sub_df['Actual']
    rmse = mean_squared_error(actual, pred, squared=False)
    r, _ = pearsonr(actual, pred)
    sns.regplot(
        x=actual, y=pred, ax=ax,
        scatter_kws={'alpha': 0.7, 'color': color, 's': 25, 'edgecolor': 'black', 'linewidths': 0.3},
        line_kws={'color': 'black', 'linestyle': '--'}, truncate=False
    )
    ax.plot(xlim, ylim, 'k--', lw=0.8)
    ax.set_xlim(*xlim)
    ax.set_ylim(*ylim)
    ax.set_title(f"{model}", fontsize=font_size + 2, fontweight='bold')
    ax.tick_params(labelsize=font_size - 0.01)
    ax.set_xlabel("")
    ax.set_ylabel("")
    if model == "Hybrid Model":
        ax.text(
            0.95, 0.05,
            f"$\\bf{{R^2 = {r2:.2f}}}$\\n$\\bf{{RMSE = {rmse:.2f}}}$\\n$\\bf{{Pearson\\'s\\ r = {r:.2f}}}$",
            transform=ax.transAxes,
            fontsize=font_size - 0.5,
            verticalalignment='bottom',
            horizontalalignment='right',
            bbox=dict(boxstyle="round", facecolor="white", edgecolor='gray', alpha=0.85),
            fontweight='bold',
            fontname='Arial'
        )
    else:
        ax.text(
            0.95, 0.05,
            f"$R^2$ = {r2:.2f}\\nRMSE = {rmse:.2f}\\nPearson's r = {r:.2f}",
            transform=ax.transAxes,
            fontsize=font_size - 0.5,
            verticalalignment='bottom',
            horizontalalignment='right',
            bbox=dict(boxstyle="round", facecolor="white", edgecolor='gray', alpha=0.85)
        )
fig.text(0.525, 0.01, "Observed a-Ratio (%)", ha='center', fontsize=font_size + 8, fontweight='bold')
fig.text(0.04, 0.55, "Predicted a-Ratio (%)", va='center', rotation='vertical', fontsize=font_size + 8, fontweight='bold')
plt.subplots_adjust(left=0.08, bottom=0.10, right=0.97, top=0.94, wspace=0.16, hspace=0.27)
plt.savefig("path/to/a_ratio_scatter.png", dpi=800)
plt.show()
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
✅ Hybrid α-ratio: R² = 0.9767, RMSE = 2.24, Pearson r = 0.9884
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
/opt/anaconda3/lib/python3.12/site-packages/sklearn/metrics/_regression.py:492: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'.
  warnings.warn(
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